PhD Fellowship in Computer Vision and Machine Learning
Deep learning has revolutionised the field of computer vision, but requires access to large homogeneous datasets. Humans in contrast can learn new concepts from remarkably few labeled examples by leveraging information from a diverse set of sources (unlabelled examples, related tasks, etc.). This ability has been termed visual fast mapping in the psychology literature. The goal of this PhD project is to develop new machine learning techniques that support visual fast mapping being data-efficient and having the ability to leverage information from many different data sources. The new techniques will be tested on data sets of medical images and scenes for autonomous systems. The research is expected to impact both medical imaging and the way people interact with and train AI systems.
The PhD position will be based in the Cambridge Machine Learning Group, supervised by Dr. Richard E. Turner. Dr. Aditya Nori (Microsoft Research) and Prof. Andrew Blake will co-supervise. The funding for this position comes from the Microsoft Research PhD Scholarship Programme.
We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in computer vision and machine learning.
A typical duration of a PhD in the machine learning group is four years.
Applicants must formally apply through the GRADSAF system at the University of Cambridge by the deadline, indicating “PhD in Engineering” as the course and denoting 'Turner' as the supervisor. This position is fully funded for UK and EU students.
Deadline: May 21st 2018
Applications from outstanding individuals may be considered after this time, but this may adversely impact your chances for admission. Moreover, applications will be considered on a rolling basis and
Further information about completing the admissions forms:
The Machine Learning Group is based in the Department of Engineering, not Computer Science.
We will assess your application on three criteria:
academic performance (make sure to ensure evidence for strong academic achievement e.g. position in year, awards etc.)
references (clearly your references will need to be strong, they should also mention evidence of excellence as quotes will be drawn from them)
research (detail your research experience, especially that which relates to machine learning and computer vision)
The form asks for a research proposal. Here we would like you to read around the research area and develop some initial ideas in this direction. We do not offer individual advice or feedback on the proposal as it is part of the assessment and want to be fair to all candidates. The research proposal should be about 2 pages long and can be attached to your application (you can indicate that you proposal is attached in the 1500 character count Research Summary box). This aspect of the application does not carry a huge amount of weight so do not spend a large amount of time on it. Please also attach a recent CV to your application too.
✔️ @ApplyTime
Deep learning has revolutionised the field of computer vision, but requires access to large homogeneous datasets. Humans in contrast can learn new concepts from remarkably few labeled examples by leveraging information from a diverse set of sources (unlabelled examples, related tasks, etc.). This ability has been termed visual fast mapping in the psychology literature. The goal of this PhD project is to develop new machine learning techniques that support visual fast mapping being data-efficient and having the ability to leverage information from many different data sources. The new techniques will be tested on data sets of medical images and scenes for autonomous systems. The research is expected to impact both medical imaging and the way people interact with and train AI systems.
The PhD position will be based in the Cambridge Machine Learning Group, supervised by Dr. Richard E. Turner. Dr. Aditya Nori (Microsoft Research) and Prof. Andrew Blake will co-supervise. The funding for this position comes from the Microsoft Research PhD Scholarship Programme.
We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in computer vision and machine learning.
A typical duration of a PhD in the machine learning group is four years.
Applicants must formally apply through the GRADSAF system at the University of Cambridge by the deadline, indicating “PhD in Engineering” as the course and denoting 'Turner' as the supervisor. This position is fully funded for UK and EU students.
Deadline: May 21st 2018
Applications from outstanding individuals may be considered after this time, but this may adversely impact your chances for admission. Moreover, applications will be considered on a rolling basis and
Further information about completing the admissions forms:
The Machine Learning Group is based in the Department of Engineering, not Computer Science.
We will assess your application on three criteria:
academic performance (make sure to ensure evidence for strong academic achievement e.g. position in year, awards etc.)
references (clearly your references will need to be strong, they should also mention evidence of excellence as quotes will be drawn from them)
research (detail your research experience, especially that which relates to machine learning and computer vision)
The form asks for a research proposal. Here we would like you to read around the research area and develop some initial ideas in this direction. We do not offer individual advice or feedback on the proposal as it is part of the assessment and want to be fair to all candidates. The research proposal should be about 2 pages long and can be attached to your application (you can indicate that you proposal is attached in the 1500 character count Research Summary box). This aspect of the application does not carry a huge amount of weight so do not spend a large amount of time on it. Please also attach a recent CV to your application too.
✔️ @ApplyTime
The 16th International Workshop on Acoustic Signal Enhancement (IWAENC) will be held at Hitotsubashi Hall in Tokyo, Japan, on September 17 – 20, 2018. IWAENC was established in 1993, originally as the International Workshop on Acoustic Echo and Noise Control (this is how the abbreviation IWAENC came into use). It is the leading workshop in the signal processing community addressing theoretical and technical issues related to acoustic and speech signal acquisition and processing. The four-day program consists of oral and poster presentations, keynote talks, and demonstrations.
We look forward to welcoming you to IWAENC 2018 in Tokyo, Japan.
Hiroshi Saruwatari, Shoji Makino
The IWAENC 2018 Organising Committee
http://www.iwaenc2018.org
✔️ @ApplyTime
We look forward to welcoming you to IWAENC 2018 in Tokyo, Japan.
Hiroshi Saruwatari, Shoji Makino
The IWAENC 2018 Organising Committee
http://www.iwaenc2018.org
✔️ @ApplyTime
Several postdoc and research scientist positions are available in my group at KAUST (King Abdullah University of Science and Technology), Thuwal, Saudi Arabia.
https://www.kaust.edu.sa/en
https://en.wikipedia.org/wiki/King_Abdullah_University_of_Science_and_Technology
Suitable backgrounds: machine learning, optimization, high performance computing, deep learning, computer vision, applied mathematics, randomized algorithms, randomized numerical linear algebra.
Starting date: Fall 2018 / Spring 2019 (exact starting date is flexible)
Duration: 1-3 years
If interested, send your cv to me by email.
Peter Richtarik
Associate Professor of Computer Science, KAUST
http://www.maths.ed.ac.uk/~prichtar/
✔️ @ApplyTime
https://www.kaust.edu.sa/en
https://en.wikipedia.org/wiki/King_Abdullah_University_of_Science_and_Technology
Suitable backgrounds: machine learning, optimization, high performance computing, deep learning, computer vision, applied mathematics, randomized algorithms, randomized numerical linear algebra.
Starting date: Fall 2018 / Spring 2019 (exact starting date is flexible)
Duration: 1-3 years
If interested, send your cv to me by email.
Peter Richtarik
Associate Professor of Computer Science, KAUST
http://www.maths.ed.ac.uk/~prichtar/
✔️ @ApplyTime
PhD position in the area of analysis/prediction of human behaviour from temporal sequences in the wild.
A joint PhD position between 3D SAM (IMT Lille Douai / CRIStAL (UMR CNRS), France, and MICC, University of Florence, Italy).
We are looking for motivated, talented candidates for a PhD position in the area of analysis/prediction of human behaviour from temporal sequences in the wild.
This PhD program will take place at the Media Integration and Communication Center (MICC) at University of Florence (UNIFI), Italy, and the 3D SAM CRSItAL (UMR CNRS) at IMT Lille Douai, France. MICC is a pioneer laboratory in Computer Vision, and 3D SAM has a long experience in the analysis of 3D human behaviour understanding. The PhD student will work under the supervision of Prof. Stefano Berretti (MICC/UNIFI), Prof. A. Del Bimbo (MICC/UNIFI), Prof. Pietro Pala (MICC/UNIFI) and Prof. Mohamed Daoudi (IMT Lille Douai, CRIStAL).
Context and Objectives: In the last few years, we have assisted to a proliferation of methods for automatically analysing human action/behaviour by using data acquired with RGB-D cameras. Though these considerable efforts resulted in remarkable advancements in the field, existing solutions are still far from being deployable in real application contexts. There are some main reasons for this: (i) current RGB-D devices used to acquire benchmark datasets are constrained to work indoor at short distance; (ii) datasets include short sequences, where subjects show posed actions; (iii) the analysis is mostly oriented to action detection and recognition, while important tasks as interaction and prediction are not considered. In this proposal, we devise to move a step forward in the analysis of human action/behaviour, with the ultimate goal of making this field entering a more mature dimension, where concrete impact in real world applications is expected. On the one hand, we will propose innovative methods for the analysis and prediction of temporal sequences. To this end, we aim to combine geometric methods that model the temporal dimension through non-linear manifolds, with the discriminative power of Deep Learning methods. On the other, we will apply these methods to RGB-D data acquired with new depth sensors that can work outdoor and at distance. This will allow long sequences, large variability and spontaneous human behaviour. All these aspects draw a challenging and completely new scenario for RGB-D solutions that goes well beyond what proposed in the existing literature.
Student profile: Strong preference will be given to candidates with experience in Computer Vision and Deep Learning, and a good knowledge of written and spoken English. The following expertise is especially considered:
• Excellent record of academic and/or professional achievement
• Very good English skills, written and spoken (B2 level appreciated). Good written and spoken communication skills in Italian will be appreciated
• Strong mathematical skills
• Solid programming skills
• Strong interests in one or more of the involved research areas (machine learning, computer vision, high performance computing)
The position is for duration of three years.
Eligibility criteria:
• A Master degree in Computer Science, Computer Engineering, Mathematics, Physics or closely related disciplines
• Appropriate experience to undertake PhD research in the specified area.
How to apply: Candidates are invited to send their CV before June 15th 2018, detailing their academic background with courses and grades during the last two years to mohamed.daoudi@imt-lille-douai.fr, stefano.berretti@unifi.it
✔️ @ApplyTime
A joint PhD position between 3D SAM (IMT Lille Douai / CRIStAL (UMR CNRS), France, and MICC, University of Florence, Italy).
We are looking for motivated, talented candidates for a PhD position in the area of analysis/prediction of human behaviour from temporal sequences in the wild.
This PhD program will take place at the Media Integration and Communication Center (MICC) at University of Florence (UNIFI), Italy, and the 3D SAM CRSItAL (UMR CNRS) at IMT Lille Douai, France. MICC is a pioneer laboratory in Computer Vision, and 3D SAM has a long experience in the analysis of 3D human behaviour understanding. The PhD student will work under the supervision of Prof. Stefano Berretti (MICC/UNIFI), Prof. A. Del Bimbo (MICC/UNIFI), Prof. Pietro Pala (MICC/UNIFI) and Prof. Mohamed Daoudi (IMT Lille Douai, CRIStAL).
Context and Objectives: In the last few years, we have assisted to a proliferation of methods for automatically analysing human action/behaviour by using data acquired with RGB-D cameras. Though these considerable efforts resulted in remarkable advancements in the field, existing solutions are still far from being deployable in real application contexts. There are some main reasons for this: (i) current RGB-D devices used to acquire benchmark datasets are constrained to work indoor at short distance; (ii) datasets include short sequences, where subjects show posed actions; (iii) the analysis is mostly oriented to action detection and recognition, while important tasks as interaction and prediction are not considered. In this proposal, we devise to move a step forward in the analysis of human action/behaviour, with the ultimate goal of making this field entering a more mature dimension, where concrete impact in real world applications is expected. On the one hand, we will propose innovative methods for the analysis and prediction of temporal sequences. To this end, we aim to combine geometric methods that model the temporal dimension through non-linear manifolds, with the discriminative power of Deep Learning methods. On the other, we will apply these methods to RGB-D data acquired with new depth sensors that can work outdoor and at distance. This will allow long sequences, large variability and spontaneous human behaviour. All these aspects draw a challenging and completely new scenario for RGB-D solutions that goes well beyond what proposed in the existing literature.
Student profile: Strong preference will be given to candidates with experience in Computer Vision and Deep Learning, and a good knowledge of written and spoken English. The following expertise is especially considered:
• Excellent record of academic and/or professional achievement
• Very good English skills, written and spoken (B2 level appreciated). Good written and spoken communication skills in Italian will be appreciated
• Strong mathematical skills
• Solid programming skills
• Strong interests in one or more of the involved research areas (machine learning, computer vision, high performance computing)
The position is for duration of three years.
Eligibility criteria:
• A Master degree in Computer Science, Computer Engineering, Mathematics, Physics or closely related disciplines
• Appropriate experience to undertake PhD research in the specified area.
How to apply: Candidates are invited to send their CV before June 15th 2018, detailing their academic background with courses and grades during the last two years to mohamed.daoudi@imt-lille-douai.fr, stefano.berretti@unifi.it
✔️ @ApplyTime
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ResearchTopics2018_IIT-PAVIS.pdf
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Postdoc Position in Machine Learning for Genomics Research at University of Tennessee Health Science Center
Denoscription
Applications are invited for a postdoctoral fellow position in the computational systems biology lab (http://compbio.uthsc.edu/) at University of Tennessee Health Science Center. The successful candidate will be involved in developing deep learning algorithms for genomics research and precision medicine. The Department of Genetics, Genomics and Informatics and the Center for Integrative and Translational Genomics provide a highly dynamic and collaborative environment fostering scientific breakthroughs.
Qualifications
The candidate must have obtained his/her Ph.D. degree in Bioinformatics, Computer Science or a related field. We are expecting high motivation and ability to work independently, as well as part of a research team. The candidate must have acquired a solid publication record and have excellent programming skills. Research experience in machine learning is required. Preference will be given to candidates with knowledge of deep learning.
Please send a CV, a cover letter describing your previous work and career goals, putative starting date and the contact information for three references to Dr. Yan Cui (ycui2@uthsc.edu).
Salary will be commensurate with relevant experience and is competitive for postdoctoral research fellows. The position includes an excellent benefits package (http://www.uthsc.edu/postdoc/benefits.php). Located in Memphis, a dynamic Mid-South city rich in culture, history, diversity, music and cuisine, the University of Tennessee Health Science Center is one of the largest, most comprehensive academic health centers in the United States with a solid commitment to postdoctoral training. UTHSC is an EEO/AA/Title VI/Title IX/Section 504/ADA/ADEA/V institution in the provision of its education and employment programs and services.
✔️ @ApplyTime
Denoscription
Applications are invited for a postdoctoral fellow position in the computational systems biology lab (http://compbio.uthsc.edu/) at University of Tennessee Health Science Center. The successful candidate will be involved in developing deep learning algorithms for genomics research and precision medicine. The Department of Genetics, Genomics and Informatics and the Center for Integrative and Translational Genomics provide a highly dynamic and collaborative environment fostering scientific breakthroughs.
Qualifications
The candidate must have obtained his/her Ph.D. degree in Bioinformatics, Computer Science or a related field. We are expecting high motivation and ability to work independently, as well as part of a research team. The candidate must have acquired a solid publication record and have excellent programming skills. Research experience in machine learning is required. Preference will be given to candidates with knowledge of deep learning.
Please send a CV, a cover letter describing your previous work and career goals, putative starting date and the contact information for three references to Dr. Yan Cui (ycui2@uthsc.edu).
Salary will be commensurate with relevant experience and is competitive for postdoctoral research fellows. The position includes an excellent benefits package (http://www.uthsc.edu/postdoc/benefits.php). Located in Memphis, a dynamic Mid-South city rich in culture, history, diversity, music and cuisine, the University of Tennessee Health Science Center is one of the largest, most comprehensive academic health centers in the United States with a solid commitment to postdoctoral training. UTHSC is an EEO/AA/Title VI/Title IX/Section 504/ADA/ADEA/V institution in the provision of its education and employment programs and services.
✔️ @ApplyTime
Postdoc Position in Machine Learning at University of Tennessee Health Science Center
Denoscription
Applications are invited for a postdoctoral fellow position in the computational systems biology lab (http://compbio.uthsc.edu/) at University of Tennessee Health Science Center. The successful candidate will be involved in developing deep learning algorithms for genomics research and precision medicine. The Department of Genetics, Genomics and Informatics and the Center for Integrative and Translational Genomics provide a highly dynamic and collaborative environment fostering scientific breakthroughs.
Qualifications
The candidate must have obtained his/her Ph.D. degree in Bioinformatics, Computer Science or a related field. We are expecting high motivation and ability to work independently, as well as part of a research team. The candidate must have acquired a solid publication record and have excellent programming skills. Research experience in machine learning is required. Preference will be given to candidates with knowledge of deep learning.
Please send a CV, a cover letter describing your previous work and career goals, putative starting date and the contact information for three references to Dr. Yan Cui (ycui2@uthsc.edu).
Salary will be commensurate with relevant experience and is competitive for postdoctoral research fellows. The position includes an excellent benefits package (http://www.uthsc.edu/postdoc/benefits.php). Located in Memphis, a dynamic Mid-South city rich in culture, history, diversity, music and cuisine, the University of Tennessee Health Science Center is one of the largest, most comprehensive academic health centers in the United States with a solid commitment to postdoctoral training. UTHSC is an EEO/AA/Title VI/Title IX/Section 504/ADA/ADEA/V institution in the provision of its education and employment programs and services.
✔️ @ApplyTime
Denoscription
Applications are invited for a postdoctoral fellow position in the computational systems biology lab (http://compbio.uthsc.edu/) at University of Tennessee Health Science Center. The successful candidate will be involved in developing deep learning algorithms for genomics research and precision medicine. The Department of Genetics, Genomics and Informatics and the Center for Integrative and Translational Genomics provide a highly dynamic and collaborative environment fostering scientific breakthroughs.
Qualifications
The candidate must have obtained his/her Ph.D. degree in Bioinformatics, Computer Science or a related field. We are expecting high motivation and ability to work independently, as well as part of a research team. The candidate must have acquired a solid publication record and have excellent programming skills. Research experience in machine learning is required. Preference will be given to candidates with knowledge of deep learning.
Please send a CV, a cover letter describing your previous work and career goals, putative starting date and the contact information for three references to Dr. Yan Cui (ycui2@uthsc.edu).
Salary will be commensurate with relevant experience and is competitive for postdoctoral research fellows. The position includes an excellent benefits package (http://www.uthsc.edu/postdoc/benefits.php). Located in Memphis, a dynamic Mid-South city rich in culture, history, diversity, music and cuisine, the University of Tennessee Health Science Center is one of the largest, most comprehensive academic health centers in the United States with a solid commitment to postdoctoral training. UTHSC is an EEO/AA/Title VI/Title IX/Section 504/ADA/ADEA/V institution in the provision of its education and employment programs and services.
✔️ @ApplyTime
Postdoctoral Position in the Interactive Media Lab at the University of Toronto
Re-posting to the post-doc category. Note revised due date of *May 11*. All applicants with user interface / machine learning experience welcome. Please send cover letter and CV to Dr. Mark Chignell at chignell@mie.utoronto.ca if interested.
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Machine Learning Postdoctoral Position at U. of Toronto (Interactive Media Lab in Industrial Engineering)
We are seeking a postdoctoral candidate who holds a PhD in engineering or computer science, to work in the area of innovative user interfaces between humans and smart agents. Experience in machine learning, mixed integer linear programming optimization, deep learning, Bayesian networks, data mining, or a related data-processing field is required. Strong programming skills are required. Familiarity with Android operating system is preferred
Experience with human factors and user interface design is an asset. The main role of the candidate will be to collaborate with an industry partner and the university research team members on the development of novel user interfaces for an intelligent smart phone assistant. An additional role is to provide strong leadership to MASc and PhD students in the team.
Excellent communication skills, strong independent research skills, and sensitivity to industry partner direction are required. The candidate will be expected to work independently, provide leadership to an interdisciplinary team of graduate students, produce publishable results, and publish frequently.
Initial funding for 1 year is available. An extension of funding to 2 years is possible, depending on project success and availability of funds.
The application package (to be emailed to Prof. M. Chignell) should include a cover letter and CV, including a list of 3 professional references.
**Deadline: May 11, 2018
Dr. Mark Chignell
Professor, Industrial Engineering and Computer Science
Department of Mechanical & Industrial Engineering
Faculty of Applied Science & Engineering
University of Toronto
5 King's College Road
Toronto, ON Canada M5S 3G8
Phone: +1 (416) 978-8951
(No Voicemail, send messages by email)
Fax: +1 (416) 978-7753
Email: chignell@mie.utoronto.ca
Web: https://www.mie.utoronto.ca/mie/faculty/chignell
https://imedia.mie.utoronto.ca/
✔ @ApplyTime
Re-posting to the post-doc category. Note revised due date of *May 11*. All applicants with user interface / machine learning experience welcome. Please send cover letter and CV to Dr. Mark Chignell at chignell@mie.utoronto.ca if interested.
===
Machine Learning Postdoctoral Position at U. of Toronto (Interactive Media Lab in Industrial Engineering)
We are seeking a postdoctoral candidate who holds a PhD in engineering or computer science, to work in the area of innovative user interfaces between humans and smart agents. Experience in machine learning, mixed integer linear programming optimization, deep learning, Bayesian networks, data mining, or a related data-processing field is required. Strong programming skills are required. Familiarity with Android operating system is preferred
Experience with human factors and user interface design is an asset. The main role of the candidate will be to collaborate with an industry partner and the university research team members on the development of novel user interfaces for an intelligent smart phone assistant. An additional role is to provide strong leadership to MASc and PhD students in the team.
Excellent communication skills, strong independent research skills, and sensitivity to industry partner direction are required. The candidate will be expected to work independently, provide leadership to an interdisciplinary team of graduate students, produce publishable results, and publish frequently.
Initial funding for 1 year is available. An extension of funding to 2 years is possible, depending on project success and availability of funds.
The application package (to be emailed to Prof. M. Chignell) should include a cover letter and CV, including a list of 3 professional references.
**Deadline: May 11, 2018
Dr. Mark Chignell
Professor, Industrial Engineering and Computer Science
Department of Mechanical & Industrial Engineering
Faculty of Applied Science & Engineering
University of Toronto
5 King's College Road
Toronto, ON Canada M5S 3G8
Phone: +1 (416) 978-8951
(No Voicemail, send messages by email)
Fax: +1 (416) 978-7753
Email: chignell@mie.utoronto.ca
Web: https://www.mie.utoronto.ca/mie/faculty/chignell
https://imedia.mie.utoronto.ca/
✔ @ApplyTime
Postdoc position in data mining and machine learning
Applications are invited for a postdoctoral fellow position of “data mining and machine learning” in the Department of Ophthalmology and the Department of Genetics, Genomics, and Informatics (GGI) at the University of Tennessee Health Science Center in Memphis. The candidate will be supervised jointly by Drs. Rob Williams, Siamak Yousefi, and Hao Chen (part of the center of excellence in machine learning). The highly-motivated postdoctoral fellow will work in broad computational ophthalmology and computational biology areas. We are currently working on retinal functional, structural, and genomic data utilizing both classical machine learning approaches and the state-of-the-art deep learning. We have access to large datasets in our centers and across the world. The Department of Ophthalmology and the Department of Genetics, Genomics, and Informatics extended research teams provide a highly dynamic and collaborative environment fostering scientific breakthroughs. This position is for a one-year appointment with the potential to be renewed.
Job
Postdoctoral Fellows
Primary Location
US-Tennessee-Memphis
Organization
Genetics, Genomics & Informatics
Campus/Institute
Memphis
Schedule
Full-time
Job Posting
Apr 5, 2018, 11:33:42 AM
The candidate must have obtained his/her Ph.D. degree in computer science, data science, software engineering, computer engineering, electrical engineering, bioinformatics, or similar fields. We are expecting high motivation and ability to work independently, as well as part of a research team. The candidate must have acquired a solid publication record and have excellent writing skills. Strong verbal and communication skills in English are required. The candidate will play a major role in the preparation of manunoscripts and grants that arise from this work.
Research experience in machine learning, data mining, statistical methods, and computing is required. The prospective candidates should be highly experienced in Python and R programming. Preference will be given to candidates with knowledge of Google Tensorflow backend (or other similar backends) and Keras deep learning library (or other similar libraries). Experience in Matlab programming or past vision/genetic research is a plus.
For More Information See
https://academic.uthsc.edu/faculty/Robert_Williams.html
https://academic.uthsc.edu/faculty/facepage.php?netID=syousef1&personnel_id=351869
https://syousefy.wixsite.com/yousefilab
https://www.uthsc.edu/neuroscience/faculty/h_chen.php
To apply, please send a CV, a cover letter describing your previous work and career goals, putative starting date and the contact information for three references tosiamak.yousefi@uthsc.edu .
✔ @ApplyTime
Applications are invited for a postdoctoral fellow position of “data mining and machine learning” in the Department of Ophthalmology and the Department of Genetics, Genomics, and Informatics (GGI) at the University of Tennessee Health Science Center in Memphis. The candidate will be supervised jointly by Drs. Rob Williams, Siamak Yousefi, and Hao Chen (part of the center of excellence in machine learning). The highly-motivated postdoctoral fellow will work in broad computational ophthalmology and computational biology areas. We are currently working on retinal functional, structural, and genomic data utilizing both classical machine learning approaches and the state-of-the-art deep learning. We have access to large datasets in our centers and across the world. The Department of Ophthalmology and the Department of Genetics, Genomics, and Informatics extended research teams provide a highly dynamic and collaborative environment fostering scientific breakthroughs. This position is for a one-year appointment with the potential to be renewed.
Job
Postdoctoral Fellows
Primary Location
US-Tennessee-Memphis
Organization
Genetics, Genomics & Informatics
Campus/Institute
Memphis
Schedule
Full-time
Job Posting
Apr 5, 2018, 11:33:42 AM
The candidate must have obtained his/her Ph.D. degree in computer science, data science, software engineering, computer engineering, electrical engineering, bioinformatics, or similar fields. We are expecting high motivation and ability to work independently, as well as part of a research team. The candidate must have acquired a solid publication record and have excellent writing skills. Strong verbal and communication skills in English are required. The candidate will play a major role in the preparation of manunoscripts and grants that arise from this work.
Research experience in machine learning, data mining, statistical methods, and computing is required. The prospective candidates should be highly experienced in Python and R programming. Preference will be given to candidates with knowledge of Google Tensorflow backend (or other similar backends) and Keras deep learning library (or other similar libraries). Experience in Matlab programming or past vision/genetic research is a plus.
For More Information See
https://academic.uthsc.edu/faculty/Robert_Williams.html
https://academic.uthsc.edu/faculty/facepage.php?netID=syousef1&personnel_id=351869
https://syousefy.wixsite.com/yousefilab
https://www.uthsc.edu/neuroscience/faculty/h_chen.php
To apply, please send a CV, a cover letter describing your previous work and career goals, putative starting date and the contact information for three references tosiamak.yousefi@uthsc.edu .
✔ @ApplyTime
academic.uthsc.edu
UTHSC Faculty facepage : ROBERT W. WILLIAMS, Ph.D
Established in 1911, The University of Tennessee Health Science Center aims to improve human health through education, research, clinical care and public service. The UT Health Science Center campuses include colleges of Allied Health Sciences, Dentistry…
#N3441
✅ Funded PhD programmes; in biology with a focus in epigenetics, neurobiology, and quantitative biology; at Friedrich Miescher Institute; in Switzerland
⏱ Deadline: #May 01, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/Bq4qv2
✅ Funded PhD programmes; in biology with a focus in epigenetics, neurobiology, and quantitative biology; at Friedrich Miescher Institute; in Switzerland
⏱ Deadline: #May 01, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/Bq4qv2
#N3442
✅ Funded PhD programmes; in Dynamic Biosensors GmbH, Marie Curies Early Stage Researcher; at Munich university; in Germany
⏱ Deadline: #May 01, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/juLKoq
✅ Funded PhD programmes; in Dynamic Biosensors GmbH, Marie Curies Early Stage Researcher; at Munich university; in Germany
⏱ Deadline: #May 01, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/juLKoq
#N3443
✅ Funded PhD programmes; in the field of Statistical / Machine Learning; at University of Wollongong; in Australia
⏱ Deadline: #May 01, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/CkMeBK
✅ Funded PhD programmes; in the field of Statistical / Machine Learning; at University of Wollongong; in Australia
⏱ Deadline: #May 01, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/CkMeBK
#N3444
✅ Funded PhD programmes; in the field of Chemistry and Food Chemistry; at Technische Universität Dresden; in Germany
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/DWS9FT
✅ Funded PhD programmes; in the field of Chemistry and Food Chemistry; at Technische Universität Dresden; in Germany
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/DWS9FT
#N3445
✅ Funded Postdoctoral programme; in the field of CNatural Diversity RCUK Grow Colombia; at Earlham Institute; in UK
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/xqvcCD
✅ Funded Postdoctoral programme; in the field of CNatural Diversity RCUK Grow Colombia; at Earlham Institute; in UK
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/xqvcCD
#N3446
✅ Funded PhD programme; in the field of The Molecular Basis of Diatom Adhesion and Motility; at Technische Universität Dresden; in Germany
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/rGKUrj
✅ Funded PhD programme; in the field of The Molecular Basis of Diatom Adhesion and Motility; at Technische Universität Dresden; in Germany
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/rGKUrj
#N3447
✅ Up to two scholarships bachelor’s degree programme; in the field of Engineering, Medical and health sciences; at HAN University; in Netherlands
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/bfqfxV
✅ Up to two scholarships bachelor’s degree programme; in the field of Engineering, Medical and health sciences; at HAN University; in Netherlands
⏱ Deadline: #May 02, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/bfqfxV
#N3448
✅ Full and Partial IED Undergraduate Scholarships bachelor’s degree programme; in the fields of Design, Fashion, Visual Arts, Communication and Restoration; at Milan, Cagliari, Como, Florence, Rome, Turin, and Venice Universities; in Italy
⏱ Deadline: #May 03, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/2Hsv37
✅ Full and Partial IED Undergraduate Scholarships bachelor’s degree programme; in the fields of Design, Fashion, Visual Arts, Communication and Restoration; at Milan, Cagliari, Como, Florence, Rome, Turin, and Venice Universities; in Italy
⏱ Deadline: #May 03, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/2Hsv37
#N3449
✅ Scholarships masters, MPhil/PhD degree programme; in various fields; at SOAS University of London; in UK
⏱ Deadline: #May 03, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/LuXuwP
✅ Scholarships masters, MPhil/PhD degree programme; in various fields; at SOAS University of London; in UK
⏱ Deadline: #May 03, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/LuXuwP
#N3450
✅ Scholarships for Foundation and Diploma programme; in various fields; at University Pathway; in Australia
⏱ Deadline: #May 04, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/VYdGDS
✅ Scholarships for Foundation and Diploma programme; in various fields; at University Pathway; in Australia
⏱ Deadline: #May 04, 2018
✔️ https://news.1rj.ru/str/ApplyTime
🌐 https://goo.gl/VYdGDS
Harnessing a cancer patient’s immune system to fight their disease is a promising new frontier in cancer treatment. Our multi-site machine learning group is collaborating with experts in cancer immunotherapy at several leading cancer centers and universities (https://www.standuptocancer.org/press_release/view/Convergence_Teams_Microsoft). Our goal is to figure out how to better target therapies to patients by learning from biomedical data. We have an open RA position starting immediately. This is a contract position through June 30, 2019, with potential to extend. The position is ideal for a recent undergraduate or M. Eng student wishing to gain research experience prior to pursuing a Ph.D. Interviews will start immediately.
https://www.microsoft.com/en-us/research/publication/cancer-immunotherapy-machine-learning-research-assistant-job-denoscription/
✔ @ApplyTime
https://www.microsoft.com/en-us/research/publication/cancer-immunotherapy-machine-learning-research-assistant-job-denoscription/
✔ @ApplyTime
Stand Up To Cancer
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Stand Up To Cancer funds the newest and most promising cancer treatments to help patients. Learn about our efforts to make every cancer patient a survivor.
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Harnessing a cancer patient’s immune system to fight their disease is a promising new frontier in cancer treatment. Our multi-site machine learning group is collaborating with experts in cancer immunotherapy at several leading cancer centers and universities…
The national research council (NRC) Canada is looking for three researchers (“research officers") in machine learning applied to natural language processing, computer vision, engineering and a few other fields.
NRC is a great place for young researchers to develop while maintaining contact with university, and have an impact in real-world applications.
If you have a PhD, significant experience designing and building novel Machine Learning/AI systems, and a good publication record in top conferences and journals, let us know by applying from the official posting page:
https://recruitment-recrutement.nrc-cnrc.gc.ca/job/Ottawa-Machine-Learning%2C-Research-Officer-ON/357572817/
✔️ @ApplyTime
NRC is a great place for young researchers to develop while maintaining contact with university, and have an impact in real-world applications.
If you have a PhD, significant experience designing and building novel Machine Learning/AI systems, and a good publication record in top conferences and journals, let us know by applying from the official posting page:
https://recruitment-recrutement.nrc-cnrc.gc.ca/job/Ottawa-Machine-Learning%2C-Research-Officer-ON/357572817/
✔️ @ApplyTime